PNP (Perspective-N-Point) and PNL (Perspective-N-Line) are the most commonly used methods for camera pose estimation. However, most methods are based on the hypothesis of the pinhole camera model, which ignore camera distortion’s effects. Considering the influences of camera distortion, we proposed to solve the camera pose directly by using distorted lines. In this paper, we first undistort the lines according to distortion model, then use LSD algorithm extract 2D undistorted lines from the image. Having matched 2D/3D lines, the PNL (Perspective-N-Line) was used finally to solve the camera pose. Through experiments on synthetic images and real images, it turns out that our method is effective and feasible for pose estimation.
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Camera pose estimation based on distorted lines
Semantic Scholar · Computer Science · 2019
Abstract
PNP (Perspective-N-Point) and PNL (Perspective-N-Line) are the most commonly used methods for camera pose estimation. However, most methods are based on the hypothesis of the pinhole camera model, which ignore camera distortion’s effects. Considering the influences of camera distortion, we proposed to solve the camera pose directly by using distorted lines. In this paper, we first undistort the lines according to distortion model, then use LSD algorithm extract 2D undistorted lines from the image. Having matched 2D/3D lines, the PNL (Perspective-N-Line) was used finally to solve the camera pose. Through experiments on synthetic images and real images, it turns out that our method is effective and feasible for pose estimation.